Graduate School

Data Sciences Foundations - Certificate

Make Big Data Meaningful

The data deluge being experienced in our markets today requires technical experts with the skills for collecting, handling, and analyzing large datasets. Data scientists are in high demand in every industry. The structured, meaningful information provided by data scientists becomes the basis for industrial innovation and strategy. Use complex, quantitative algorithms in data analysis, governance, and validation.

Data science has been listed as one of the top three jobs in America on Glassdoor. The median base salary is approximately $108,000 and there are currently more than 6,500 job openings in the field. 

Michigan Tech’s Certificate in Data Science Foundations brings together students from diverse fields with interest in data analysis, data science, and computing tools. Students develop skills in fundamental data science techniques, including predictive modeling, data mining, information management, data analytics, and data visualization. Students also gain team-building and communication skills through collaborative projects, using their technical skills to analyze data generated by real-world problems. Together, students hone their ability to harness information from data analytics for social and industrial impact.  

What you need to know

This certificate requires a total of 9-credits and can be completed in a two-semester sequence or spread over three semesters.

Only open to students enrolled in a graduate program and applicants who are not currently enrolled in any graduate program at Michigan Tech. Students who complete the Certificate in Data Science Foundations also have the option of continuing their education through the MS in Data Science program.

Students who complete the Certificate in Data Science Foundations will demonstrate their core proficiency in data science foundations, understand the application of data science foundations to specific problems, and can apply the professional skills of a data scientist (data, written, and oral communication).